Data-Intensive architecture for scientific knowledge discovery

Atkinson, Malcolm and Liew, Chee Sun and Galea, Michelle and Martin, Paul and Krause, Amrey and Mouat, Adrian and Corcho, Oscar and Snelling, D. (2012). Data-Intensive architecture for scientific knowledge discovery. "Distributed And Parallel Databases", v. 30 (n. 5-6); pp. 307-324. ISSN 0926-8782.


Title: Data-Intensive architecture for scientific knowledge discovery
  • Atkinson, Malcolm
  • Liew, Chee Sun
  • Galea, Michelle
  • Martin, Paul
  • Krause, Amrey
  • Mouat, Adrian
  • Corcho, Oscar
  • Snelling, D.
Item Type: Article
Título de Revista/Publicación: Distributed And Parallel Databases
Date: October 2012
Volume: 30
Freetext Keywords: Knowledge discovery, Workflow management system, Descubrimiento de conocimientos, Sistema de gestión del flujo de trabajo.
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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This paper presents a data-intensive architecture that demonstrates the ability to support applications from a wide range of application domains, and support the different types of users involved in defining, designing and executing data-intensive processing tasks. The prototype architecture is introduced, and the pivotal role of DISPEL as a canonical language is explained. The architecture promotes the exploration and exploitation of distributed and heterogeneous data and spans the complete knowledge discovery process, from data preparation, to analysis, to evaluation and reiteration. The architecture evaluation included large-scale applications from astronomy, cosmology, hydrology, functional genetics, imaging processing and seismology.

Funding Projects

FP7215024ADMIREUnspecifiedAdvanced Data Mining and Integration Research for Europe

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Item ID: 16379
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Deposited by: Memoria Investigacion
Deposited on: 11 Jul 2013 14:57
Last Modified: 31 Oct 2014 12:00
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